Penetrating 3-D Imaging at 4- and 25-m Range Using a Submillimeter-Wave Radar

We show experimentally that a high-resolution imaging radar operating at 576–605 GHz is capable of detecting weapons concealed by clothing at standoff ranges of 4–25 m. We also demonstrate the critical advantage of 3-D image reconstruction for visualizing hidden objects using active-illumination coherent terahertz imaging. The present system can image a torso with <1 cm resolution at 4 m standoff in about five minutes. Greater standoff distances and much higher frame rates should be achievable by capitalizing on the bandwidth, output power, and compactness of solid state Schottky-diode based terahertz mixers and multiplied sources

Submillimetre wave 3D imaging radar for security applications

There is ongoing worldwide interest in finding solutions to enhance the security of civilians at airports, borders and high risk public areas in ways which are safe, ethical and streamlined. One promising approach is to use submillimetre wave 3D imaging radar to detect concealed threats as it offers the advantages of high volumetric resolution (~1 cm3) with practically sized antennas (<0.5 m) such that even quite small objects can be resolved through clothing. The Millimetre Wave Group at the University of St Andrews has been developing submillimetre wave 3D imaging radars for security applications since 2007. A significant goal is to achieve near real-time frame rates of at least 10 Hz, to cope with dynamic scenes, over wide fields of view at short range with high pixel counts. We review the radar systems we have developed at 340 and 220 GHz and the underpinning technologies which we have employed to realise these goals.PostprintNon peer reviewe

Emerging Approaches for THz Array Imaging: A Tutorial Review and Software Tool

Accelerated by the increasing attention drawn by 5G, 6G, and Internet of Things applications, communication and sensing technologies have rapidly evolved from millimeter-wave (mmWave) to terahertz (THz) in recent years. Enabled by significant advancements in electromagnetic (EM) hardware, mmWave and THz frequency regimes spanning 30 GHz to 300 GHz and 300 GHz to 3000 GHz, respectively, can be employed for a host of applications. The main feature of THz systems is high-bandwidth transmission, enabling ultra-high-resolution imaging and high-throughput communications; however, challenges in both the hardware and algorithmic arenas remain for the ubiquitous adoption of THz technology. Spectra comprising mmWave and THz frequencies are well-suited for synthetic aperture radar (SAR) imaging at sub-millimeter resolutions for a wide spectrum of tasks like material characterization and nondestructive testing (NDT). This article provides a tutorial review of systems and algorithms for THz SAR in the near-field with an emphasis on emerging algorithms that combine signal processing and machine learning techniques. As part of this study, an overview of classical and data-driven THz SAR algorithms is provided, focusing on object detection for security applications and SAR image super-resolution. We also discuss relevant issues, challenges, and future research directions for emerging algorithms and THz SAR, including standardization of system and algorithm benchmarking, adoption of state-of-the-art deep learning techniques, signal processing-optimized machine learning, and hybrid data-driven signal processing algorithms...Comment: Submitted to Proceedings of IEE

Computational polarimetric microwave imaging

We propose a polarimetric microwave imaging technique that exploits recent advances in computational imaging. We utilize a frequency-diverse cavity-backed metasurface, allowing us to demonstrate high-resolution polarimetric imaging using a single transceiver and frequency sweep over the operational microwave bandwidth. The frequency-diverse metasurface imager greatly simplifies the system architecture compared with active arrays and other conventional microwave imaging approaches. We further develop the theoretical framework for computational polarimetric imaging and validate the approach experimentally using a multi-modal leaky cavity. The scalar approximation for the interaction between the radiated waves and the target---often applied in microwave computational imaging schemes---is thus extended to retrieve the susceptibility tensors, and hence providing additional information about the targets. Computational polarimetry has relevance for existing systems in the field that extract polarimetric imagery, and particular for ground observation. A growing number of short-range microwave imaging applications can also notably benefit from computational polarimetry, particularly for imaging objects that are difficult to reconstruct when assuming scalar estimations.Comment: 17 pages, 15 figure

On the use of compressed sensing techniques for improving multistatic millimeter-wave portal-based personnel screening

This work develops compressed sensing techniques to improve the performance of an active three dimensional (3D) millimeter wave imaging system for personnel security screening. The system is able to produce a high-resolution 3D reconstruction of the whole human body surface and reveal concealed objects under clothing. Innovative multistatic millimeter wave radar designs and algorithms, which have been previously validated, are combined to improve the reconstruction results over previous approaches. Compressed Sensing techniques are used to drastically reduce the number of sensors, thus simplifying the system design and fabrication. Representative simulation results showing good performance of the proposed system are provided and supported by several sample measurement

Multiple drone type classification using machine learning techniques based on FMCW radar micro-Doppler data

Systems designed to detect the threat posed by drones should be able to both locate a drone and ideally determine its type in order to better estimate the level of threat. Previously, drone types have been discriminated using millimeter-wave Continuous Wave (CW) radar, which produces high quality micro-Doppler signatures of the drone propeller blades with fully sampled Doppler spectra. However, this method is unable to locate the target as it cannot measure range. By contrast, Frequency Modulated Continuous Wave (FMCW) data typically undersamples the micro-Doppler signatures of the blades but can be used to locate the target. In this paper we investigate FMCW features of four drones and if they can be used to discriminate the models using machine learning techniques, enabling both the location and classification of the drone. Millimeter-wave radar data are used for better Doppler sensitivity and shorter integration time. Experimentally collected data from Ttree quadcopters (DJI Phantom Standard 3, DJI Inspire 1, and Joyance JT5L-404) and a hexacopter (DJI S900) have been. For classification, feature extraction based machine learning was used. Several algorithms were developed for automated extraction of micro-Doppler strength, bulk Doppler to micro-Doppler ratio, and HERM line spacing from spectrograms. These feature values were fed to classifiers for training. The four models were classified with 85.1% accuracy. Higher accuracies greater than 95% were achieved for training using fewer drone models. The results are promising, establishing the potential for using FMCW radar to discriminate drone types.Publisher PD

Indoor Full-Body Security Screening: Radiometric Microwave Imaging Phenomenology and Polarimetric Scene Simulation

The paper discusses the scene simulation of radiometric imagers and its use to illustrate the phenomenology of full-body screening of people for weapons and threats concealed under clothing. The aperture synthesis technique is introduced as this offers benefits of wide field-of-views and large depths-of-fields in a system that is potentially conformally deployable in the confined spaces of building entrances and at airport departure lounges. The technique offers a non-invasive, non-cooperative screening capability to scrutinize all human body surfaces for illegal items. However, for indoor operation, the realization of this capability is challenging due to the low radiation temperature contrasts in imagery. The contrast is quantified using a polarimetric radiometric layer model of the clothed human subject concealing threats. A radiation frequency of 20 GHz was chosen for the simulation as system component costs here are relatively low and the attainable half-wavelength spatial resolution of 7.5 mm is sufficient for screening. The contrasts against the human body of the threat materials of metal, zirconia ceramic, carbon fiber, nitrogen-based energetic materials, yellow beeswax, and water were calculated to be ≤7 K. Furthermore, the model indicates how some threats frequency modulate the radiation temperatures by ~ ±1 K. These results are confirmed by experiments using a radiometer measuring left-hand circularly polarized radiation. It is also shown using scene simulation how circularly polarized radiation has benefits for reducing false alarms and how threat objects appear in canyon regions of the body, such as between the legs and in the armpits